The singular vector approach to the analysis of perturbation growth in the atmosphere

This dissertation applies linear algebra to the study of perturbation growth in atmospheric flows. Maximally-growing perturbations are identified from singular vector analysis of the time-evolving flow. Given a system characterized by a linear propagator L(t0,t), which describes the time evolution of small perturbations x between time t0 and t around a time-evolving trajectory, an inner product (..;..)E on the tangent space of the perturbations defined by a matrix E and its associated norm ||..||E, the problem can be stated as: Find the phase space directions x for which ||x(t)||E/ ||x(t0)||E is maximum, where x(t)=L(t0,t)x(t0) Given the adjoint L*E of the forward propagator L, perturbation growth is gauged by computing the eigenvectors of an operator including L and L*E as factors. The eigenvectors with the largest eigenvalues define the directions with maximum growth. They are called the singular vectors of the tangent forward propagator L. First, the singular vector approach is described. Second, a barotropic model of the atmospheric flow is considered. The impact of underlying orography on singular vectors growing over different time intervals, and the role of singular vectors in explaining the maintenance of blocked flows during winter, are analyzed. Third, a 3-dimensional primitive equation model of the atmospheric flow is considered. Some aspects of the application of the singular vector technique to the study of perturbation growth in the whole atmosphere are analyzed. A physical interpretation of singular vector growth based on the application of the Eliassen-Palm theorem and on WKBJ theory is proposed. Finally, two examples of operational use of singular vectors are presented. Results show how the adjoint technique is a suitable methodology for the identification of atmospheric instabilities, and how it can be used to investigate predictability problems

Introduction to the special issue on “25 years of ensemble forecasting”

Twenty-five years ago the first operational, ensemble forecasts were issued by the European Centre for Medium-Range Weather Forecasts and the National Centers for Environmental Prediction. These centres were followed in 1996 by the Meteorological Service of Canada, and in the subsequent years by many others. Operational ensemble-based, probabilistic forecasts signed a paradigm shift in weather prediction: for the first time, forecasters and users could have reliable and accurate estimates of the range of possible future scenarios, and not just a single realization of the future. Today, ensembles are used not only to provide reliable and accurate forecasts for the short and medium range, the monthly and seasonal time-scale, but also to provide estimates of the initial state of the atmosphere, and to generate future climate projections. This article provides an overview on how we developed the early ensembles, illustrates the key characteristics of the seven operational, global, medium-range ensembles, and discusses ongoing trends to further improve ensemble performance

Weather-inspired ensemble-based probabilistic prediction of COVID-19

The objective of this work is to predict the spread of COVID-19 starting from observed data, using a forecast method inspired by probabilistic weather prediction systems operational today. Results show that this method works well for China: on day 25 we could have predicted well the outcome for the next 35 days. The same method has been applied to Italy and South Korea, and forecasts for the forthcoming weeks are included in this work. For Italy, forecasts based on data collected up to today (24 March) indicate that number of observed cases could grow from the current value of 69,176, to between 101k-180k, with a 50% probability of being between 110k-135k. For South Korea, it suggests that the number of observed cases could grow from the current value of 9,018 (as of the 23rd of March), to values between 8,500 and 9,300, with a 50% probability of being between 8,700 and 8,900. We conclude by suggesting that probabilistic disease prediction systems are possible and could be developed following key ideas and methods from weather forecasting. Having access to skilful daily updated forecasts could help taking better informed decisions on how to manage the spread of diseases such as COVID-19

Affrontare il cambiamento climatico è una 'missione possibile'

Climate change is real, and we, humans, are responsible for it. Its impact is already evident, both on the Earth system (global warming, sea-level rise, sea-ice melting, more intense and frequent extreme weather events such as heat waves and fires) and on people (famines, health issues, migrations, political tensions and conflicts). We need immediate and concrete mitigation actions aiming to reduce greenhouse gases emissions, and adaptation actions to be able to cope with the increasing changing climate. We have to reach zero-net greenhouse gases emissions as soon as possible, by reducing emissions by at least 5% a year, starting from now. Otherwise the climate change impact will become more and more severe: it will induce more injustice, and it will have a major impact on people health. We have the resources and the technologies to deal with it: we must have the courage to change and transform and deal with it. Addressing climate change is not impossible: to the contrary, it is a 'possible mission'

Effects of Global Warming on Patients with Dementia, Motor Neuron or Parkinson’s Diseases: A Comparison among Cortical and Subcortical Disorders

Exposure to global warming can be dangerous for health and can lead to an increase in the prevalence of neurological diseases worldwide. Such an effect is more evident in populations that are less prepared to cope with enhanced environmental temperatures. In this work, we extend our previous research on the link between climate change and Parkinson's disease (PD) to also include Alzheimer's Disease and other Dementias (AD/D) and Amyotrophic Lateral Sclerosis/Motor Neuron Diseases (ALS/MND). One hundred and eighty-four world countries were clustered into four groups according to their climate indices (warming and annual average temperature). Variations between 1990 and 2016 in the diseases' indices (prevalence, deaths, and disability-adjusted life years) and climate indices for the four clusters were analyzed. Unlike our previous work on PD, we did not find any significant correlation between warming and epidemiological indices for AD/D and ALS/MND patients. A significantly lower increment in prevalence in countries with higher temperatures was found for ALS/MND patients. It can be argued that the discordant findings between AD/D or ALS/MND and PD might be related to the different features of the neuronal types involved and the pathophysiology of thermoregulation. The neurons of AD/D and ALS/MND patients are less vulnerable to heat-related degeneration effects than PD patients. PD patients' substantia nigra pars compacta (SNpc), which are constitutively frailer due to their morphology and function, fall down under an overwhelming oxidative stress caused by climate warming

About correlation between centre of pressure, trunk and head sways during quiet upright stance.

In order to better understand the mechanisms of orthostatic balance, centre of pressure (CoP), trunk, and head sways were simultaneously measured during quiet upright stance, and compared to each other, looking for possible correlation. Methods - A total of 16 healthy young adults served as subjects. They were asked to keep orthostatic position for 120 s, once with open and once with closed eyes. COP sway was measured by force platform, trunk oscillation by inclinometers placed at the sternum level, trunk and head angular velocities by miniature gyroscopes, placed at the sternum and the skull vertex, respectively. Cross-correlation functions were used to compare sways measured at different levels to each other. In particular, antero-posterior (AP) and medio-lateral (ML) components of CoP sway were correlated to the homologous components of trunk oscillation, and AP and ML trunk oscillation velocities to the homologous head oscillation velocities. Results – Clear and consistent positive correlation was found between trunk and head sways. In 83% of cases, cross-correlation functions presented one sharp peak near the origin, and much lower values elsewhere. Mean correlation delays in the different conditions (open or closed eyes) and directions (AP and ML) weren't significantly different from 0 at p=0.05 (t-test). Cross-correlation functions computed inside a 20 s sliding window showed that correlation was kept all along the test duration. CoP-trunk correlation was much less clear. Cross-correlation peaks as sharp as those observed between trunk and head velocities could never be observed. However, in many instances the two sways did show almost parallel time courses. This could either extend to almost the whole test duration or be limited to shorter periods, and was much more frequent in ML than in AP plane, where, in general, the two sways appeared to be uncorrelated. in a few instances, in the AP plane they semed to be phase opposed. Discussion – Sharp cross-correlation peaks with almost no delay show that trunk and head moved almost synchronously, like one rigid body. This was consistent with the fact that in either plane (AP or ML) and vision condition (eyes open or closed) the sway velocity distributions of trunk and head were similar to each other, and the corresponding average velocity ranges were not significantly different from one another at p=0.05 (t-test). Poorer correlation between CoP and trunk sways is a likely consequence of the presence of the hip joint, and the inertia of the trunk-arms-head system, linked to this joint. This makes the trunk over the hip intrinsically less steady than the head over the neck. Interestingly enough, CoP-trunk correlation was better in ML plane than in AP one, and this may easily be explained by the different stiffness of the hip joint in the two planes, due to the different geometry. Different degrees and modes of correlation between CoP and trunk sway suggest the use of different balance strategies. It is also possible that the two sways convey different, maybe complementary, information about balance control, and it could possibly make sense to consider also trunk movements in the diagnostic approach to balance control. This conclusion is consistent with previous suggestions by different authors

Evaluation of ERA5 and CHIRPS rainfall estimates against observations across Ethiopia

Satellite-based precipitation estimates and global reanalysis products bear the promise of supporting the development of accurate and timely climate information for end users in sub-Sharan Africa. The accuracy of these global models, however, may be reduced in data-scarce regions and should be carefully evaluated. This study evaluates the performance of ERA5 reanalysis data and CHIRPS precipitation data against ground-based measurements from 167 rain gauges in Ethiopia, a region with complex topography and diverse climates. Focusing over a 38-year period (1981–2018), our study utilizes a point-to-pixel analysis to compare daily, monthly, seasonal, and annual precipitation data, conducting an evaluation based on continuous and categorical metrics. Our findings indicate that over Ethiopia CHIRPS generally outperforms ERA5, particularly in high-altitude areas, demonstrating a better capability in detecting high-intensity rainfall events. Both datasets, however, exhibit lower performance in Ethiopia's lowland regions, possibly the influence of sparse rain gauge networks informing gridded datasets. Notably, both CHIRPS and ERA5 were found to underestimate rainfall variability, with CHIRPS displaying a slight advantage in representing the erratic nature of Ethiopian rainfall. The study’s results highlight considerable performance differences between CHIRPS and ERA5 across varying Ethiopian landscapes and climatic conditions. CHIRPS’ effectiveness in high-altitude regions, especially for daily rainfall estimation, emphasizes its suitability in similar geographic contexts. Conversely, the lesser performance of ERA5 in these areas suggests a need for refined calibration and validation processes, particularly for complex terrains. These insights are essential for the application of satellite-based and reanalysis of rainfall data in meteorological, agricultural, and hydrological contexts, particularly in topographically and climatically diverse regions

Atmospheric drivers affect crop yields in Mozambique

Climate change has been inducing variations in the statistics of both the large-scale weather patterns and the local weather in many regions of the world, and these variations have been affecting several human activities, including agriculture. In this study, we look at the links between large-scale weather patterns and local weather as well as agriculture, with a specific regional focus on Mozambique between 1981 and 2019. First, we investigated linear trends and links between large-scale weather patterns and local weather in the region using the ERA5 dataset. We used the same data to investigate how climate change has been affecting the statistics of large-scale weather patterns. Then, we derived Mozambique country-level cereal yield data from FAO and linked it up with climate and weather data to assess what is the relationship between large-scale patterns and local agronomic outputs using a multiple linear regression (MLR) model with crop yield as the response variable and climate drivers as predictors. The results indicate that in Mozambique, the crop season warmed substantially and consistently with climate change-induced global warming, and the rainy season had become drier and shorter, with precipitation concentrated in fewer, more intense events. These changes in the local weather have been linked to variations in the statistics of large-scale weather patterns that characterize the (large-scale) atmospheric flow over the region. Our results indicate a negative impact on yield associated with climate change, with average yield losses of 20% for rice and 8% for maize over the analyzed period (1981–2019). This negative impact suggests that, at the country scale, further future warming during the growing season may offset some of the cereal yield gains from technological advances

System for continuous metabolic monitoring of mechanically ventilated patients

In clinical settings, due largely to the cost, size and calibration complexity of existing indirect calorimetry systems, there is seldom instrumentation available to provide reliable, continuous tracking of a mechanically ventilated patient’s metabolic output in support of proper nutrition. The atypical metabolisms associated with critically ill patients are difficult to predict and both underfeeding and overfeeding lead to negative impacts on both mortality and the recovery and healing processes. With these issues in mind, a novel ventilator-agnostic indirect calorimetry sensor design, prototype development, and validation were undertaken with the goal of enabling 24/7 metabolic monitoring of mechanically ventilated patients by means of a passive, rate-proportional side-stream sampling scheme and miniature mixing chamber. The miniature mixing chamber enables the use of small, low-cost gas concentration and flow sensing components to ensure the affordability of commercial design-for-manufacture implementations of the prototype sensor. In addition to continuous measurement of patient metabolism, the prototype sensor also enables autonomous monitoring and detection of calibration drift in the gas measurement sensors without disrupting the patient ventilation